Welcome to Stats 115 - Introduction to Bayesian Data Analysis.
For anyone interested, in an earlier version of this course you can take a look at the course website from Winter 2021. The older link may not be useful for students currently enrolled in the course. It is shared mainly for instructors and learners elsewhere.
Basic Bayesian concepts and methods with emphasis on data analysis. Special emphasis on specification of prior distributions. Includes linear, logistic, and Poisson regression. Analyses are performed using Stan with rstan package in R.
Prerequisite: STATS 120C
Recommended STATS 110
Concurrent with STATS 203
For anyone interested, in an earlier version of this course you can take a look at the course website from Winter 2021. The older link may not be useful for students currently enrolled in the course. It is shared mainly for instructors and learners elsewhere.
Basic Bayesian concepts and methods with emphasis on data analysis. Special emphasis on specification of prior distributions. Includes linear, logistic, and Poisson regression. Analyses are performed using Stan with rstan package in R.
Prerequisite: STATS 120C
Recommended STATS 110
Concurrent with STATS 203
Course Goals
By the end of this course you will be able to:
By the end of this course you will be able to:
- distinguish frequentist and Bayesian statistics;
- choose appropriate prior distributions for a Bayesian model;
- use rstan to fit Bayesian models;
- interpret model results.
Typical Week Workflow
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Monday 9 am
Weekly course content and assignments are released on this website under Schedule.
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Tuesday 6:30 - 7:30 pm
Attend office hours (recommended).
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Wednesday 6:30 - 8:30 pm
Attend synchronous session (required)
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Wednesday 9:00 pm
Problem sets are due (required).
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Thursday 6:30 - 7:30 pm
Attend office hours (optional)
Important Dates
Midterm Exam August 18, 6:30 - 8:30 pm
Final Exam (written part) September 1, 6:30 - 8:30 pm
Final Exam (oral part) to be scheduled individually during the fifth week (August 30 - Sept 3).